CCAMLR

We develop statistical models of Adélie penguin fledgling weight data collected at Béchervaise Island and use them in a power analysis as a continuation of the CEMP review. The statistical models incorporate both within- and between- season variability of fledgling weights from first principles using raw data as recommended in Southwell et al. (2004). These models should be viewed as initial attempts at incorporating multiple sources of variability rather than final products because a number of issues need further consideration. Issues to be resolved include the form and direction of change of fledgling weights with a decline in resource availability, the consideration of total chick failure during severe food shortages and a possible change in variance associated with a change in the mean value. With these issues kept in mind, the major findings from these statistical models are the potential for reducing to 30 the number of birds weighed in a single 5-day period each year. If practical, this outcome could have substantial benefits by simplifying data collection. We also discuss some of the practical issues of continuing to measure fledgling weights at Béchervaise Island either by the current or the modified methodology.

Scientific observations on fishes incidentally caught during commercial krill fisheries by F/V Niitaka Maru (5306t) were made from August 6 to September 9, 2004 to the north of South Georgia Island. Among 100 net hauls quantitatively examined, a total of 12 species belonging to 6 families of by-catch fishes were occurred in 76 trawl catches. The family Myctophidae, the most abundant taxa during the present survey, were found in 61% of hauls examined. Although only one species, Lepidonotothen larseni, was captured as by-catch of the Nototheniidae, the Nototheniidae were the next in abundance and found in 25% of hauls. Length frequency distribution of by-catch of L. larseni shows this species is composed of at least 3 different year classes. Similar pattern is also found in Gymnoscopelus nicholsi of the Myctophidae. At least in the net hauls of high krill CPUE (>20t?krill/h), few or no by-catch fish was occurred. The hauls of lower krill CPUE (

We report on the development of a carbon-budget trophic-model of the Ross Sea. We provisionally defined the food web of the Ross Sea as having the following functional compartments: birds, seals, toothed whales, baleen whales, large bentho-pelagic predatory fish (mainly adult Antarctic toothfish), pelagic and juvenile fish (mainly Antarctic silverfish), demersal fish (skates, rattails, notothenioids), cryopelagic fish, squid, macrozooplankton (including krill and salps), macrobenthos, meiobenthos, ice heterotrophs, water column zooplankton (ciliates, heterotrophic flagellates, mesozooplankton), three groups of bacteria (water column, ice, and sediment), phytoplankton, epontic algae, and three detritus groups (water column, ice, and benthic). The simple trophic model requires well over a hundred parameters, each of which has been estimated by sifting published and unpublished information. Local information on organisms in the Ross Sea was used whenever available. Where no information in the literature was available we have sought out field measurements that have not been published, or estimated values using explicit assumptions.
The model is not complete, and should be considered a work in progress. A trial budget was created to quantify carbon flow through our conceptual model of the Ross Sea ecosystem. A first run of the model was carried out, and the initial set of parameters was not found to be self-consistent i.e. they do not lead to a balanced model. The next step is to determine the range of ecosystem variables that are consistent with our current understanding of the constraints on ecosystem functioning within the bounds of uncertainty estimated for each parameter; we term this approach feasible parameter space mapping.

An assessment of the environmental processes influencing variability in the recruitment and density of Antarctic krill (Euphausia superba DANA) is important as variability in krill stocks affects the Antarctic marine ecosystem as a whole. Naganobu et al. (1999) had assessed variability in krill recruitment and density in the Antarctic Peninsula area with an environmental factor; strength of westerly winds (westerlies) determined from sea-level pressure differences across the Drake Passage, between Rio Gallegos (51°32’S, 69°17’W), Argentina, and Base Esperanza (63°24’S, 56°59’W), at the tip of the Antarctic Peninsula during 1982-1998. Fluctuations in the westerlies across the Drake Passage were referred to as the Drake Passage Oscillation Index (DPOI). They found significant correlations between krill recruitment and DPOI. Additionally, we calculated a new time series of DPOI from January 1952 to March 2005.

A survey of the Japanese R/V Kaiyo Maru was carried out to collect data simultaneously on ecological interaction of environment – Antarctic krill – whales in the Ross Sea and adjacent waters during December 2004 and February 2005. Transect lines along 165E, 175E, 180, 175W, 170W and 165W were investigated to cover hot spots which suggest high concentrated krill and whales such as the Scott Seamounts Island, the Balleny Islands, the shelf off the Victoria Land and the almost whole of the Ross Sea. The 175E and 170W lines, especially, were surveyed in detail from the surface to near the sea bottom from 60S to the edge of the Ross Ice Shelf on physical, chemical and biological parameters.

The distribution of krill females of the different maturity stages was considered to reveal the preferable bottom depths for the spawning. Calculations based on the three expanded scientific surveys and numerous data from observers revealed no statistically reliable tendency in the gravid females to move offshore to deeper waters. The possible reasons causing the spawning females distribution are discussed. It is assumed, that the most important factor determining gravid females distribution is food supply.

A key area of concern highlighted by the Scientific Committee of the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) concerns the potential overlap of the krill fishery with the foraging area of land-based predators such as seals and penguins in the Antarctic Peninsula region. The dynamics of krill in this region are strongly influenced by advective processes. A key question is therefore whether or not limitations on fishing activities (reducing their economic efficiency) are necessary given that there is a flux of krill through this region with its islands habited by predator colonies. In order to estimate the krill production actually available for predator consumption, it is necessary not only to consider “snapshot” survey estimates of krill abundance in the vicinity of a breeding colony but also the flux of krill through such areas. This paper outlines a proposed spatial modelling framework that could be used to couple flux estimates with estimates of removals by both the fishery and predators, in an attempt to quantify what level and localisation of the fishing effort might impact the predators negatively. The approach described represents work still in progress as the focus thus far has been on first developing a model of the possible impact of pelagic fishing on seal and penguin colonies on the South African west coast. The latter ecosystem shares a number of common features with the Antarctic Peninsula ecosystem in that there is a substantial advective flux of either pelagic fish or of krill, with both species serving as dominant prey items for colonies of land-based predators in the region concerned. Subject to the availability of data from both predator studies and krill surveys, the West Coast model methodology could thus straightforwardly (initially at least) be adapted to the Antarctic Peninsula region. This would permit the evaluation of a wide range of management options pertaining to the issue of taking into account the needs of other species when setting precautionary krill catch limits at an appropriate spatial scale.

This document summarizes work that we completed after submitting background document WG-EMM-05/13. Our intent here is to augment and enhance WG-EMM-05/13, and the follwing text can be attached to WG-EMM-05/13 as its third appendix. To facilitate such attachment, we start the page numbering of this appendix at page 55. This appendix contains 1) example parameterizations and results for krill movement in the KPFM, 2) errata for the main text of WG-EMM-05/13, 3) errata for and extensions to Appendix 1 of WG-EMM- 05/13, and 4) a short, annotated script of S-plus commands that we hope to follow while demonstrating our KPFM to the WG-EMM and the Workshop on Management Procedures.

The CCAMLR has recognised the need to subdivide the precautionary krill catch limit for Statistical Area 48 amongst smaller spatial units in order to minimize the localized depletion of krill in predator foraging areas. These smaller spatial units, termed small-scale management units (SSMUs), have been defined, and six candidate procedures for subdividing the catch have been identified. It is now necessary to evaluate these procedures in terms of their likely effects on krill and predator populations as well as fishery performance. This evaluation must be conducted in the context of considerable uncertainty about how the krill-predator- fishery system operates. We describe a model designed to investigate the performance of these procedures and their sensitivity to numerical and structural uncertainty. The model is spatially resolved to the level of SSMUs and surrounding oceanic areas, and it includes the transport of krill between these areas. Krill and predator population dynamics are implemented with coupled delay-difference models, which are formulated to accommodate various assumptions about the recruitment and predation processes. The fishery is represented as a simultaneous and equal competitor for available krill. Straightforward Monte Carlo simulations are used to integrate the effects of numerical uncertainty, and structural uncertainty can be assessed by comparing and merging results from multiple such simulations. We present a range of performance measures that can be used to evaluate catch-allocation procedures and assess tradeoffs between predator and fishery performance. We provide basic instructions on running the model in S-Plus and illustrate its use. Finally, we conclude that although our model necessarily simplifies a complex system, it provides a flexible framework for investigating the roles of transport, production, predation and harvesting in the operation of the krill-predator-fishery system.

Data from individual hauls carried out by krill F/V “Atlantic Navigator” operating in three fishing zones were analyzed: Elephant islands zone (48.1), South Georgias islands zone (48.3) and South Orkney islands zone (48.2). The fishing season was extended from 19/2/04 (summer 2004) to 7/4/05 (early winter 2005) with a total of 251 days of effective fishing. Descriptive study of the fishery operation was performed for the two fishing systems used: conventional fishing system (CON) and the continuous fishing system with air-bubbling suspension and suction of capture (CFS). Individual haul data were analyzed to describe differentialy catch rates (catch per day and catch per minute) of the three different fishing zones studied. The total catch registered was 41837 tonnes: 50% of this capture was obtained at South Orkney islands zone. The highest catch rate were calculated for the same fishing zone with CFS (293 kg/min) during summer 2005. The biggest krill size also corresponded to this zone and season: 50 mm total length. Sexual proportion determined when possible (summer 2005) was determined: males 64,59%, females 28,00% and immature individuals 7,38%. Predominant colour of sampled individuals was determined IC for winter season 2004 and IIC and IIB for summer to winter 2005. All data was recorded under the CCAMLR Scheme of International Scientific Observation (SC-CAMLR, 1993).